Abstract: A system and method are described for using different types of image fingerprints to detect spam. Specifically, one embodiment of the invention dynamically calculates both an image-specific signature (e.g., MD5 checksum) and a generic signature for each image and, if a specified number of images have the same generic signature but different image-specific signatures, then a feature is fired within a spam engine to indicate that the images are spam. By way of example, a computer-implemented method is described for detecting spam images within a stream of messages comprising: generating generic signatures and image-specific signatures for images within the stream of messages; determining if two or more images with matching generic signatures have different image-specific signatures; and updating a spam filtering engine to include the matching generic signatures if the number of images with matching generic signatures but different image-specific signatures reach a specified threshold value.

Abstract: A system and method are described for performing a correlative statistical analysis on a stream of email messages to identify new spam campaigns. For example, a method according to one embodiment of the invention comprises: extracting a series of patterns from a stream of incoming email messages; performing a correlation between the patterns to identify recurring patterns within the stream of email messages over a specified time period; dynamically updating a spam filtering engine to include a particular recurring pattern if the number of times the particular recurring pattern is detected within the specified time period is above a first specified threshold value.